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prediction to process optimization. The focus of this PhD project is to develop and apply machine learning methods across three interconnected tasks: 3D microstructure characterisation. The student will
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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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proficiency in English a structured, self-driven, independent approach to technical work and good collaboration skills coursework or other experiences in the following subjects are valued: optimization, linear
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to structure and prioritize your work effectively. Merits: Courses in tumor biology and immunology Experience in gene modulation (e.g., siRNA, CRISPR-Cas9) Experience working with patient-derived organoids
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to work independently, take initiative, and plan and conduct research with attention to detail, scientific rigor, and a structured, systematic approach. High motivation and strong interest in developing
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, computational methods, and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab
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of ion conductivity in complex battery materials on a large scale. Model‑generated data will be used to identify key relationships between material structure and ionic conductivity through advanced data
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dynamics. Particular emphasis is placed on opinion dynamics as well as distributed problems in coordination, optimization, and learning. The research encompasses both theoretical and computational aspects
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involve the conceptual and practical development of the methodology for electrochemically initiated time-resolved soft X-ray spectroscopy, including construction and optimization of measurement setups and
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algorithms. Our research integrates expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems